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NIPS
2008
15 years 7 months ago
Biasing Approximate Dynamic Programming with a Lower Discount Factor
Most algorithms for solving Markov decision processes rely on a discount factor, which ensures their convergence. It is generally assumed that using an artificially low discount f...
Marek Petrik, Bruno Scherrer
NIPS
1994
15 years 7 months ago
On-line Learning of Dichotomies
The performance of on-line algorithms for learning dichotomies is studied. In on-line learning, the number of examples P is equivalent to the learning time, since each example is ...
N. Barkai, H. Sebastian Seung, Haim Sompolinsky
CORR
2008
Springer
149views Education» more  CORR 2008»
15 years 6 months ago
Gaussian Belief Propagation for Solving Systems of Linear Equations: Theory and Application
The canonical problem of solving a system of linear equations arises in numerous contexts in information theory, communication theory, and related fields. In this contribution, we...
Ori Shental, Danny Bickson, Paul H. Siegel, Jack K...
TSP
2008
113views more  TSP 2008»
15 years 6 months ago
Avoiding Divergence in the Shalvi-Weinstein Algorithm
The most popular algorithms for blind equalization are the constant-modulus algorithm (CMA) and the ShalviWeinstein algorithm (SWA). It is well-known that SWA presents a higher co...
Maria D. Miranda, Magno T. M. Silva, Victor H. Nas...
PC
2002
118views Management» more  PC 2002»
15 years 5 months ago
Parallel algorithms for indefinite linear systems
Saddle-point problems give rise to indefinite linear systems that are challenging to solve via iterative methods. This paper surveys two recent techniques for solving such problem...
Ahmed H. Sameh, Vivek Sarin